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Stochastic Mixed-Integer Programming for Integrated Portfolio Planning in the LNG Supply Chain

Adrian Werner, Kristin Tolstad Uggen, Marte Fodstad, Arnt-Gunnar Lium, and Ruud Egging

Year: 2014
Volume: Volume 35
Number: Number 1
DOI: 10.5547/01956574.35.1.5
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Abstract:
We present a new model to support strategic planning by actors in the liquefied natural gas market. The model takes an integrated portfolio perspective and addresses uncertainty in future prices. Decision variables include investments and disinvestments in infrastructure and vessels, chartering of vessels, the timing of contracts, and spot market trades. The model accounts for various contract types and vessels, and it addresses losses. The underlying mathematical model is a multistage stochastic mixed-integer linear problem. Industry-motivated numerical cases are discussed as benchmarks for the potential increases in profits that can be obtained by using the model for decision support. These examples illustrate how a portfolio perspective leads to decisions different than those obtained using the traditional net present value approach. We show how explicitly considering uncertainty affects investment and contracting decisions, leading to higher profits and better utilization of capacity. In addition, model run times are competitive with current business practices of manual planning.



Stochastic Modeling of Natural Gas Infrastructure Development in Europe under Demand Uncertainty

Marte Fodstad, Ruud Egging, Kjetil Midthun, and Asgeir Tomasgard

Year: 2016
Volume: Volume 37
Number: Sustainable Infrastructure Development and Cross-Border Coordination
DOI: https://doi.org/10.5547/01956574.37.SI3.mfod
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Abstract:
We present an analysis of the optimal development of natural gas infrastructure in Europe based on the scenario studies of Holz and von Hirschhausen (2013). We use a stochastic mixed integer quadratic model to analyze the impact of uncertainty about future natural gas consumption in Europe on optimal investments in pipelines. Our data is based on results from the PRIMES model of natural gas demand and technology scenarios discussed in Knopf et al. (2013). We present a comparison between the results from the stochastic model and the expected value model, as well as an analysis of the individual scenarios. We also performed sensitivity analyses on the probabilities of the future scenarios. Comparison of the results from the stochastic model to those of a deterministic expected value model reveals a negligible Value of the Stochastic Solution. We do, however, find structurally different infrastructure solutions in the stochastic and the deterministic models. Regarding infrastructure expansions, we find that 1) the largest pipeline investments will be towards Asia, 2) there is a trend towards a larger gas supply from Africa to Europe, and 3) within Europe, eastward connections will be strengthened. Our main finding using the stochastic approach is that there is limited option value in delaying investments in natural gas infrastructure, until more information is available regarding policy and technology in 2020, due to the low costs of overcapacity.





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